Published 10 July 2023 in Audio articles • 6 min read • 
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We can’t get through a day without feeling the impact of the latest innovation in AI coming to life in real time. But it’s the tangible ramifications in the near future of this exponential impact that bewilder us all. ChatGPT is not the only thing. Copilot by Microsoft is another. Then the stock market saw Nvidia hit a trillion-dollar valuation, surpassing Tesla and Meta. Nvidia is a company that a year ago few outside of the tech sector would know or care about. It’s a company quietly making chipsets for video gamers; and it just so happens that these same chipsets can be trained for AI. A trillion-dollar capitalization is a thousand billion: a thousand unicorns.
The magnitude of change in our world, all of a sudden, becomes unfathomable. Should it be a surprise that the Writers Guild of America, with its 11,000 unionized writers, went on strike?
It’s always at these junctures, these ruptures, that some companies manage to ride on the next wave while others get left behind. Put differently: technology upheaval is always neutral. It benefits those who are future-ready. It supercharges the growth of some companies but also causes irreversible damage to those who are not ready. A question worth asking, therefore, is this: Can you tell if a company is future-ready? How do you measure readiness?
At IMD’s Center for Future Readiness, we produce a biannual ranking to measure just that. We do this through objective, rule-based measures that are calculated as a composite score. The ranking is based on seven main factors: (1) financial fundamentals, (2) investors’ expectations of future growth, (3) business diversity, (4) employee diversity/ESG, (5) research and development, (6) early results of innovation efforts, and (7) cash and debt. These seven main factors, which carry the same weight in the overall result, comprise 33 variables.
In our most recent Future Readiness Indicator, published in May, we investigated the consumer packaged goods, finance, and automobile sectors. We discovered that the top-ranking companies in each sector have the basis and foundations they need to take advantage of the next new thing. Five years ago, it was omnichannel, e-commerce, and the Internet of Things (IoT). Today, it’s generative AI. The top-ranking companies in our indicator are more capable of absorbing and responding to new trends because their executives and managers have prioritized initiatives and are able to persevere to do the hard work that is required in those new areas. Let’s look at the financial industry as an example.
Organizations must become more inclusive and diverse to thrive in the future: the business case is as a compelling as the moral imperative. How can executives foster inclusion to unlock the power of diversity, while recognizing and tackling inequity and discrimination? In the June issue of I by IMD, we explore how leaders can build organizations and design products and services that are truly inclusive.
The big trends in this industry are embedded finance and open banking. Consumers want them, regulators demand them, and investors are bullish about them. Imagine mixing finance with all kinds of commercial activities. That’s embedded finance. It’s a fancy term that describes blending financial services into non-financial services. That would represent a big world – throwing into it banking, credit, and insurance. One popular example is Buy Now Pay Later (BNPL).
This BNPL market is growing. Some project it to exceed $3 trillion by 2030. That may be why Block (ranked #6 in our indicator) paid some $29 billion to acquire BNPL tech firm Afterpay. But what is the key to success in embedded finance? The answer: easy-to-use, all-in-one experiences. This requires deep collaboration between banks, tech providers, and financial product distributors. Financial services will need to be integrated into everyday tools such as loyalty apps, digital wallets, and other online and offline shopping platforms. Making all this work together smoothly are application programming interfaces (APIs) – the behind-the-scenes tools that help different programs and organizations communicate.
That’s why top-ranking companies such as Mastercard and Visa have been relentlessly investing in APIs for years. They make sure consumers can use their network to clear PayPal transactions. They make sure crypto giant Coinbase can use them for the peer-to-peer exchange of digital goods minted as NFTs. Whether you are signing up for Apple Pay, Google Pay, Revolut, or Uber, Mastercard and Visa are the easiest options to pick, and third-party merchants are likely to accept them.
Mastercard and Visa don’t see themselves as credit card companies. They started off that way, but that’s ancient history. They are now technology firms that facilitate commercial activities. It doesn’t matter if you draw down your credit line, use fiat money, or cryptocurrencies – that is all possible with Mastercard and Visa.
The consequence, of course, is that these organizations have made themselves very easy to work with. Whether you are Apple, with its strict requirements for data security, or a fintech upstart in Vietnam that needs speed and simplicity, Mastercard, for example, can cater to you. It’s an organization that can pull data and information across the enterprise if needed. It’s an organization where technology expertise can move around the world. It’s an organization where its salespeople can mix and match the features of a product and customize it for the needs of a local startup at ease and without complicated internal coordination.
“Mastercard and Visa don’t see themselves as credit card companies. They started off that way, but that’s ancient history. They are now technology firms that facilitate commercial activities.”
Now, ask yourselves, if not them, then who in the industry can take the greatest advantage of generative AI to further automate workflow, product development, or customer support? To harness AI, you need data that’s clean and ready. You need a clear architecture that facilitates data exchange and sharing. When you have invested in an API-first strategy for so long, you are ready to take advantage of generative AI.
That’s maybe why we observe, also in the automotive and consumer package goods sectors, that our rankings don’t jump all that much year by year – it takes hard work and perseverance to move up the ranking. No great company emerges overnight. The thought of a burning platform that propels a company to greatness is a myth. Instead, look to those that are best and continuously prepared to pivot to take advantage of the latest trends or to buffer themselves against the worst. No matter what environment they are in, they are ahead of the competition. That, to me, seems like a fair definition of being future-ready.
Jialu Shan, a research fellow at the Global Center for Digital Business Transformation at IMD, contributed to this article.
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